What is Docker Integration

The MCP server is a tool for managing Docker containers using natural language commands, allowing users to compose, introspect, and manage containers seamlessly.

Use cases

This server is designed for server administrators needing to manage Docker engines remotely, tinkerers experimenting with open-source applications, and AI enthusiasts pushing the boundaries of language model capabilities in container management.

How to use

To use the MCP server, install it via PyPi or Docker, configure your MCP servers file with appropriate commands, and then engage with the LLM to compose containers in a plan+apply loop that allows for interactive feedback and planning.

Key features

Key features include the ability to compose containers using natural language, introspect and debug running containers, manage Docker volumes for persistent data, and retrieve logs and stats for containers.

Where to use

The MCP server can be utilized on local machines for development and experimentation, as well as on remote servers for production deployments, facilitating seamless Docker management from any environment.

🐋 Docker MCP server

An MCP server for managing Docker with natural language!

🪩 What can it do?

• 🚀 Compose containers with natural language
• 🔍 Introspect & debug running containers
• 📀 Manage persistent data with Docker volumes

❓ Who is this for?

• Server administrators: connect to remote Docker engines for e.g. managing a
  public-facing website.
• Tinkerers: run containers locally and experiment with open-source apps
  supporting Docker.
• AI enthusiasts: push the limits of that an LLM is capable of!

Demo

A quick demo showing a WordPress deployment using natural language:

https://github.com/user-attachments/assets/65e35e67-bce0-4449-af7e-9f4dd773b4b3

🏎️ Quickstart

Install

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json

On Windows: %APPDATA%/Claude/claude_desktop_config.json

"mcpServers": {
  "mcp-server-docker": {
    "command": "uvx",
    "args": [
      "mcp-server-docker"
    ]
  }
}

docker build -t mcp-server-docker .

"mcpServers": {
  "mcp-server-docker": {
    "command": "docker",
    "args": [
      "run",
      "-i",
      "--rm",
      "-v",
      "/var/run/docker.sock:/var/run/docker.sock",
      "mcp-server-docker:latest"
    ]
  }
}

📝 Prompts

🎻 docker_compose

Use natural language to compose containers. See above for a demo.

Provide a Project Name, and a description of desired containers, and let the LLM
do the rest.

This prompt instructs the LLM to enter a plan+apply loop. Your interaction
with the LLM will involve the following steps:

1. You give the LLM instructions for which containers to bring up
2. The LLM calculates a concise natural language plan and presents it to you
3. You either:
   • Apply the plan
   • Provide the LLM feedback, and the LLM recalculates the plan

Examples

• name: nginx, containers: “deploy an nginx container exposing it on port
  9000”
• name: wordpress, containers: “deploy a WordPress container and a supporting
  MySQL container, exposing Wordpress on port 9000”

Resuming a Project

When starting a new chat with this prompt, the LLM will receive the status of
any containers, volumes, and networks created with the given project name.

This is mainly useful for cleaning up, in-case you lose a chat that was
responsible for many containers.

📔 Resources

The server implements a couple resources for every container:

• Stats: CPU, memory, etc. for a container
• Logs: tail some logs from a container

🔨 Tools

Containers

• list_containers
• create_container
• run_container
• recreate_container
• start_container
• fetch_container_logs
• stop_container
• remove_container

Images

• list_images
• pull_image
• push_image
• build_image
• remove_image

Networks

• list_networks
• create_network
• remove_network

Volumes

• list_volumes
• create_volume
• remove_volume

🚧 Disclaimers

Sensitive Data

DO NOT CONFIGURE CONTAINERS WITH SENSITIVE DATA. This includes API keys,
database passwords, etc.

Any sensitive data exchanged with the LLM is inherently compromised, unless the
LLM is running on your local machine.

If you are interested in securely passing secrets to containers, file an issue
on this repository with your use-case.

Reviewing Created Containers

Be careful to review the containers that the LLM creates. Docker is not a secure
sandbox, and therefore the MCP server can potentially impact the host machine
through Docker.

For safety reasons, this MCP server doesn’t support sensitive Docker options
like --privileged or --cap-add/--cap-drop. If these features are of interest
to you, file an issue on this repository with your use-case.

🛠️ Configuration

This server uses the Python Docker SDK’s from_env method. For configuration
details, see
the documentation.

Connect to Docker over SSH

This MCP server can connect to a remote Docker daemon over SSH.

Simply set a ssh:// host URL in the MCP server definition:

"mcpServers": {
  "mcp-server-docker": {
    "command": "uvx",
    "args": [
      "mcp-server-docker"
    ],
    "env": {
      "DOCKER_HOST": "ssh://[email protected]"
    }
  }
}

💻 Development

Prefer using Devbox to configure your development environment.

See the devbox.json for helpful development commands.

After setting up devbox you can configure your Claude MCP config to use it:

  "docker": {
    "command": "/path/to/repo/.devbox/nix/profile/default/bin/uv",
    "args": [
      "--directory",
      "/path/to/repo/",
      "run",
      "mcp-server-docker"
    ]
  },